Current xenogeneic mouse models cannot evaluate on-target off-tumor adverse effect, hindering the development of chimeric antigen receptor (CAR) T cell therapies for solid tumors, due to limited human/mouse cross-reactivity of antibodies used in CAR and sever graft-versus-host disease induced by administered human T cells. We have evaluated safety and antitumor efficacy of CAR-T cells targeting glypican-1 (GPC1) overexpressed in various solid tumors. GPC1-specific human and murine CAR-T cells generated from our original anti-human/mouse GPC1 antibody showed strong antitumor effects in xenogeneic and syngeneic mouse models, respectively. Importantly, the murine CAR-T cells enhanced endogenous T cell responses against a non-GPC1 tumor antigen through the mechanism of antigen-spreading and showed synergistic antitumor effects with anti-PD-1 antibody without any adverse effects in syngeneic models. Our study shows the potential of GPC1 as a CAR-T cell target for solid tumors and the importance of syngeneic and xenogeneic models for evaluating their safety and efficacy.

Various immune mediators have crucial roles in the pathogenesis of intraocular diseases. Machine learning can be used to automatically select and weigh various predictors to develop models maximizing predictive power. However, these techniques have not yet been extensively applied studies focused on intraocular diseases. We evaluated whether five machine learning algorithms applied to the data of immune mediator levels in aqueous humor can accurately predict the actual diagnoses of 17 selected intraocular diseases, and identified which immune mediators drive the predictive power of a machine learning model. Cross-sectional study. 512 eyes with diagnoses of 17 intraocular diseases. Aqueous humor samples were collected, and the concentrations of 28 immune mediators were determined using a cytometric bead array. Each immune mediator was ranked according to its importance using five machine learning algorithms: random forest (RF), linear support vector machine (SVM), radial basis function SVM, decision tree and naïve Bayes classifier. Stratified k-fold cross-validation was used in evaluation of algorithms with dataset divided into training and test datasets. The algorithms were evaluated in terms of precision, recall, accuracy, F-score, area under the receiver operating characteristics curve, area under the precision-recall curve and mean decrease in Gini index. Among the five machine learning models, RF yielded the highest classification accuracy in multi-class differentiation of 17 intraocular diseases. The RF prediction models for vitreoretinal lymphoma, acute retinal necrosis, endophthalmitis, rhegmatogenous retinal detachment, and primary open angle glaucoma achieved the highest classification accuracy, precision, and recall. RF recognized vitreoretinal lymphoma, acute retinal necrosis, endophthalmitis, rhegmatogenous retinal detachment and primary open angle glaucoma with the top five F-scores. The three highest-ranking relevant immune mediators were IL-10, IP-10 and angiogenin for prediction of vitreoretinal lymphoma; Mig, IFN-γ and IP-10 for acute retinal necrosis; and IL-6, G-CSF and IL-8 for endophthalmitis. RF algorithms based on 28 immune mediators in aqueous humor successfully predicted the diagnosis of vitreoretinal lymphoma, acute retinal necrosis, and endophthalmitis. Overall, the findings of the present study contribute to increased knowledge on new biomarkers that can potentially facilitate diagnosis of intraocular diseases in the future.

The activities of various metabolic pathways can influence the pathogeneses of autoimmune diseases, and intrinsic metabolites can potentially be used to diagnose diseases. However, the metabolomic analysis of patients with uveitis has not yet been conducted. Here, we profiled the serum metabolomes of patients with three major forms of uveitis (Behҫet’s disease (BD), sarcoidosis, and Vogt-Koyanagi-Harada disease (VKH)) to identify potential biomarkers. This study included 19 BD, 20 sarcoidosis, and 15 VKH patients alongside 16 healthy control subjects. The metabolite concentrations in their sera were quantified using liquid chromatography with time-of-flight mass spectrometry. The discriminative abilities of quantified metabolites were evaluated by four comparisons: control vs. three diseases, and each disease vs. the other two diseases (such as sarcoidosis vs. BD + VKH). Among 78 quantified metabolites, 24 kinds of metabolites showed significant differences in these comparisons. Four multiple logistic regression models were developed and validated. The area under the receiver operating characteristic (ROC) curve (AUC) in the model to discriminate disease groups from control was 0.72. The AUC of the other models to discriminate sarcoidosis, BD, and VKH from the other two diseases were 0.84, 0.83, and 0.73, respectively. This study provides potential diagnostic abilities of sarcoidosis, BD, and VKH using routinely available serum samples that can be collected with minimal invasiveness.

High-throughput RNA sequencing (RNA-seq) uses massive parallel sequencing technology, allowing the unbiased analysis of genome-wide transcription levels and tumor mutation status. Immunoglobulin G4-related ophthalmic disease (IgG4-ROD) is a fibroinflammatory disease characterized by the enlargement of the ocular adnexal tissues. We analyzed RNA expression levels via RNA-seq in the biopsy specimens of three patients diagnosed with IgG4-ROD. Mucosa-associated lymphoid tissue (MALT) lymphoma, reactive lymphoid hyperplasia (RLH), normal lacrimal gland tissue, and adjacent adipose tissue were used as the controls (n = 3 each). RNA-seq was performed using the NextSeq 500 system, and genes with |fold change| ≥ 2 and p < 0.05 relative to the controls were defined as differentially expressed genes (DEGs) in IgG4-ROD. To validate the results of RNA-seq, real-time polymerase chain reaction (PCR) was performed in 30 IgG4-ROD and 30 orbital MALT lymphoma tissue samples. RNA-seq identified 35 up-regulated genes, including matrix metallopeptidase 12 (MMP12) and secreted phosphoprotein 1 (SPP1), in IgG4-ROD tissues when compared to all the controls. Many pathways related to the immune system were included when compared to all the controls. Expressions of MMP12 and SPP1 in IgG4-ROD tissues were confirmed by real-time PCR and immunohistochemistry. In conclusion, we identified novel DEGs, including those associated with extracellular matrix degradation, fibrosis, and inflammation, in IgG4-ROD biopsy specimens. These data provide new insights into molecular pathogenetic mechanisms and may contribute to the development of new biomarkers for diagnosis and molecular targeted drugs.

(1) Purpose: Primary vitreoretinal lymphoma (PVRL) is associated with poor prognosis because most of the patients with PVRL develop central nerve system lymphoma. The prognostic biomarker of PVRL is largely unknown. Cluster analysis has been used to identify phenotypic groups within various diseases. In this study, we aimed to describe clinical features of patients with PVRL grouped by clustering analysis and to identify biomarkers for predicting survival prognosis in patients with PVRL. (2) Materials and Methods: Forty patients with PVRL were divided into two groups by clustering analysis using clinical data. Clinical features of the two groups were compared. (3) Result: Clustering analysis classified patients into groups A and B. The survival rate during the follow-up period was significantly lower in group B than in group A (p = 0.03). Serum IgG, serum IgA, vitreous IL-10 and vitreous IL-10 to IL-6 ratio were significantly different between groups A and B (p = 0.03, 0.005, 0.008 and 0.03, respectively). Receiver operating characteristic (ROC) curves generated for the four variables indicated that serum IgA was most suitable for the prediction of prognosis. Patients with serum IgA below 184 mg/dL obtained from the ROC curve had a lower three-year survival rate (p = 0.03) and more episodes of recurrence of lymphoma (3.2 times versus 1.8 times, p = 0.02) compared with patients with serum IgA above 184 mg/dL. (4) Conclusion: The survival rate was significantly different in PVRL patients classified into two groups by clustering analysis. Patients with lower serum IgA had more recurrences and poorer survival than patients with higher IgA.

Various immune mediators identified to date are associated with the development of advanced forms of diabetic retinopathy (DR), such as proliferative DR and diabetic macular edema, although the exact pathophysiological mechanisms of early stages of DR such as simple DR remain unclear. We determined the immune mediator profile in the aqueous humor of eyes with simple DR. Fifteen eyes of fifteen patients with simple DR were studied. Twenty-two eyes of twenty-two patients with cataracts and no DR served as controls. Undiluted aqueous humor samples were collected, and a cytometric bead array was used to determine the aqueous humor concentrations of 32 immune mediators comprising 13 interleukins (IL), interferon-γ, interferon-γ-inducible protein-10 (IP-10), monocyte chemoattractant protein-1, macrophage inflammatory protein (MIP)-1α, MIP-1β, regulated on activation, normal T cell expressed and secreted (RANTES), monokine induced by interferon-γ, basic fibroblast growth factor (bFGF), Fas ligand, granzyme A, granzyme B, interferon-inducible T-cell alpha chemoattractant (ITAC), fractalkine, granulocyte macrophage colony-stimulating factor, granulocyte colony-stimulating factor (G-CSF), vascular endothelial growth factor (VEGF), angiogenin, tumor necrosis factor-α, and CD40 ligand. Among the 32 immune mediators, 10 immune mediators, including bFGF, CD40 ligand, fractalkine, G-CSF, IL-6, IL-8, MIP-α, MIP-1β, and VEGF, showed significantly higher aqueous humor concentrations and the Fas ligand had significantly lower concentration (p < 0.05) in eyes with simple DR compared with control eyes. Of these 10 cytokines with significant concentration alteration, protein–protein interaction analysis revealed that 8 established an intricate interaction network. Various immune mediators may contribute to the pathogenesis of simple DR. Attention should be given to the concentrations of immune mediators in ocular fluids even in simple DR. Large-scale studies are warranted to assess whether altered aqueous humor concentrations of these 10 immune mediators are associated with an increased risk of progression to advanced stages of DR.